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ContextFrom Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms
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- Authors
- Zhang Kai, He Xinyue, Yao Jingang
- Venue
- arXiv — preprint, not yet peer-reviewed
- Published
- 2026-04-29
- ID
- arXiv:2604.25707
How to cite it
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APA
Kai, Z., Xinyue, H., & Jingang, Y. (2026). From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms. arXiv — preprint, not yet peer-reviewed. https://arxiv.org/abs/2604.25707
MLA
Kai, Zhang, et al. "From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms." arXiv — preprint, not yet peer-reviewed, 2026, https://arxiv.org/abs/2604.25707.
BibTeX
@article{kai2026from,
title = {From Citation Selection to Citation Absorption: A Measurement Framework for Generative Engine Optimization Across AI Search Platforms},
author = {Zhang Kai and He Xinyue and Yao Jingang},
journal = {arXiv — preprint, not yet peer-reviewed},
year = {2026},
url = {https://arxiv.org/abs/2604.25707},
}What it is
Preprint, not yet peer-reviewed. Zhang Kai, He Xinyue and Yao Jingang propose separating source selection from how much a cited page contributes to an AI-generated answer. Their analysis of 602 prompts compares ChatGPT, Google AI Overview/Gemini and Perplexity; descriptive associations do not establish a causal recipe for ranking or visibility.
Topics
Added Nov 13, 2026 · 0 opens
